Zobrazeno 1 - 10
of 10 424
pro vyhledávání: '"Rask A"'
Incremental full configuration interaction (iFCI) is polynomial-cost approach to the FCI limit of electronic structure. This article introduces the many-body basis set amelioration (MBBSA) method, which is designed to allow iFCI to be applicable to l
Externí odkaz:
http://arxiv.org/abs/2410.13001
Autor:
Fajstrup, Lisbeth, Fasy, Brittany Terese, Li, Wenwen, Mezrag, Lydia, Rask, Tatum, Tombari, Francesca, Urbančič, Živa
The Gromov--Hausdorff distance measures the similarity between two metric spaces by isometrically embedding them into an ambient metric space. In this work, we introduce an analogue of this distance for metric spaces endowed with directed structures.
Externí odkaz:
http://arxiv.org/abs/2408.14394
Autor:
Menczer, Andor, van Damme, Maarten, Rask, Alan, Huntington, Lee, Hammond, Jeff, Xantheas, Sotiris S., Ganahl, Martin, Legeza, Örs
We report cutting edge performance results for a hybrid CPU-multi GPU implementation of the spin adapted ab initio Density Matrix Renormalization Group (DMRG) method on current state-of-the-art NVIDIA DGX-H100 architectures. We evaluate the performan
Externí odkaz:
http://arxiv.org/abs/2407.07411
Autor:
Kook, Lucas, Lundborg, Anton Rask
Valid statistical inference is crucial for decision-making but difficult to obtain in supervised learning with multimodal data, e.g., combinations of clinical features, genomic data, and medical images. Multimodal data often warrants the use of black
Externí odkaz:
http://arxiv.org/abs/2402.14416
Autor:
Rask, Christian D., Lucani, Daniel E.
We introduce RAGE, an image compression framework that achieves four generally conflicting objectives: 1) good compression for a wide variety of color images, 2) computationally efficient, fast decompression, 3) fast random access of images with pixe
Externí odkaz:
http://arxiv.org/abs/2402.05974
Autor:
Kuntz, Gabriel, Huang, Junxiang, Rask, Mitchell, Lindgren-Ruby, Alex, Shinsato, Jacob Y., Bi, Dapeng, Tabatabai, A. Pasha
Living objects are able to consume chemical energy and process information independently from others. However, living objects can coordinate to form ordered groups such as schools of fish. This work considers these complex groups as living materials
Externí odkaz:
http://arxiv.org/abs/2312.09375
Autor:
Lundborg, Anton Rask, Pfister, Niklas
Existing effect measures for compositional features are inadequate for many modern applications for two reasons. First, modern datasets with compositional covariates, for example in microbiome research, display traits such as high-dimensionality and
Externí odkaz:
http://arxiv.org/abs/2311.18501
Autor:
Baltazar Nunes, James Humphreys, Nathalie Nicolay, Toon Braeye, Izaak Van Evercooren, Christian Holm Hansen, Ida Rask Moustsen-Helms, Chiara Sacco, Massimo Fabiani, Jesús Castilla, Iván Martínez-Baz, Hinta Meijerink, Ausenda Machado, Patricia Soares, Rickard Ljung, Nicklas Pihlström, Anthony Nardone, Sabrina Bacci, Susana Monge
Publikováno v:
Expert Review of Vaccines, Vol 23, Iss 1, Pp 1085-1090 (2024)
Background We aimed to estimate XBB.1.5 vaccine effectiveness (VE) against COVID-19-related hospitalizations and deaths during BA.2.86/JN.1 predominance, among EU/EEA individuals with ≥65-years.Research design and methods We linked electronic healt
Externí odkaz:
https://doaj.org/article/eafb3041a9b34ec5bef9e8604c8a60ba
Autor:
Hao Li, Sumit Agrawal, Ning Zhu, Daniela I. Cacciabue, Marcelo N. Rivolta, Douglas E. H. Hartley, Dan Jiang, Hanif M. Ladak, Gerard M. O’Donoghue, Helge Rask‑Andersen
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Traditional approaches to the human cochlear nerve have been impeded by its bony encasement deep inside the skull base. We present an innovative, minimally invasive, therapeutic pathway for direct access to the nerve to deliver novel regener
Externí odkaz:
https://doaj.org/article/fd62f2847f6b4e789a16fba60130a406
Discovering causal relationships from observational data is a fundamental yet challenging task. Invariant causal prediction (ICP, Peters et al., 2016) is a method for causal feature selection which requires data from heterogeneous settings and exploi
Externí odkaz:
http://arxiv.org/abs/2309.12833